Field of the Invention
The present invention relates to a technique of identifying an object in an image.
Description of the Related Art
There have been proposed many techniques of comparing input image data with image data registered in advance so as to identify a category registered in advance to which an object expressed by the input image data belongs. A detailed example of such object identification is personal authentication. This technique identifies a person using a feature such as a face or fingerprint unique to the individual, and is called face authentication or fingerprint authentication. Categories in personal authentication are a name and an ID capable of specifying an individual. In object identification including personal authentication, the image of each object to be identified needs to be registered in advance as a registered image together with a name or ID before implementation of identification. Identification can actually be implemented after the registration. When the image (to be referred to as an input image hereinafter) of an object to be identified is input, it is compared with each of registered images registered in advance. If a registered image matches the input image, a registered object corresponding to the registered image is output as an identification result. If none of the registered images matches the input image, “no-object found” is output. In this specification, identifying the category of an object will mean determining the difference between the individuals of objects (for example, the difference between persons) hereinafter.
As a considerable technical method of identifying a person from a facial image, the pixels of the facial image itself are defined as feature amounts and directly compared with each other. In this method, however, variations in the pixel values depending on the orientation and expression of the face and the illumination condition are larger than those depending on the difference between persons, and it is difficult to identify the person. To solve this problem, there have been proposed a number of methods of extracting only a plurality of local regions representing features of an individual from a facial image and comparing corresponding local regions with each other. However, even with this method, it is difficult to completely remove the above-described variations, and local regions that are useful for identification and those that are not are formed. To select only the local regions useful for identification, there have been proposed methods of, for example, selecting a predetermined number of local regions in descending order of the degree of similarity obtained as a result of comparison of corresponding local regions between images (for example, Japanese Patent No. 4803214).
The technique disclosed in Japanese Patent No. 4803214 selects a predetermined number of local regions in descending order of the degree of similarity out of the degrees of similarity of a plurality of local regions. This is based on a concept that only local regions without variations, that is, having high degrees of similarity in an image are used. However, the optimum number of local regions that should be used varies depending on the degree of variation in the shooting condition between images. If the shooting conditions are close, the variation is small, and a larger number of local regions are desired to be used. If the shooting conditions are different, a smaller number of local regions are desired to be used.